Process control systems control industrial processes by means of various field devices connected to the process, such as regulating devices, control devices, transducers, transmitters, and the like. A typical field device is a control valve provided with a valve controller. Devices known as intelligent field devices are equipped with control logic or software which make it possible to control the field device locally, for example by means of a suitable control algorithm, to collect both status and measurement data, and/or to communicate with an automation system or a field device management system. A field device, such as an intelligent control valve, is typically controlled by a process controller applying a suitable control algorithm on the basis of the measurement results (feedback) obtained from the process and the set values. Thus, a so-called control loop is formed. A large industrial process may include a plurality, even hundreds, of such control loops.
Control loops (control circuits) are tuned during installation to produce a desired process operation as well as possible, and they can be controlled when process performance is to be upgraded, or for some other reason. There are a variety of indices and measurements representing the performance of a control system and a process. They all illustrate this important matter from different points of view. In each specific situation, suitable indices and measurements should be selected to describe the process performance in question. Performance indices are also interdependent, and the upgrading of performance on the basis of one index may weaken the performance when assessed according to some other performance index. Further, when a large number of control circuits and control loops are used, it is difficult for a control room personnel to perceive and analyse the effect of different process controls and the real performance of a control loop or a sub-process in relation to the desired performance.
A prior art method for monitoring control circuit performance is a simple control error measurement and monitoring. Data related to the control operations are collected on a substantially on-line basis, and different summaries are computed during the monitoring period on the basis of the control errors. These summaries include control error absolute value, control error square, variability, etc. Such methods are commonly used.
Another known solution for monitoring control circuit performance includes methods that aim at detecting control circuit oscillation. This kind of method is described for example in U.S. Pat. No. 5,719,788.
A third prior art method is to compare control circuit performance with a minimum variance control, which allows stochastic disturbances to be eliminated quicker than with other methods. In other words, an index is obtained that indicates how much better the control could operate in theory if a customized minimum variance control were in use. The user enters a process delay as a parameter, the delay being in theory an element restricting the speed of the control operation.
The above methods measure a single dimension of control performance. No information is obtained of the total condition of the circuit. For example, the above described control error measurement and monitoring fails to explain the type of the problems occurring in the control, even in the case of a major error. A major control error may occur for example because the control is saturated, there is a load disturbance or a change of mode, or because the circuit is operated in manual mode. On the other hand, certain control problems, such as individual measurement disturbances and noises or actuator oscillations do not appear unambiguously in a control error.
The detection of control circuit oscillation is a valuable piece of information as such, but similarly as control error measurement, it is an indicator that only detects a small portion of poorly functioning control circuits.
A comparison with minimum variance control does not take into account the fact that control circuits have individual speeds and different control circuits have highly differing target speeds. In addition, the speed of minimum variance control is fairly theoretical. In practice, delay is not the only factor restricting control speed.